AutoML Leaderboard
AutoML Performance
AutoML Performance Boxplot
Features Importance (Original Scale)
Scaled Features Importance (MinMax per Model)
Spearman Correlation of Models
Summary of 1_Baseline
<< Go back
Baseline Regressor (Baseline)
- n_jobs: -1
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
1.8 seconds
Metric details:
| Metric |
Score |
| MAE |
42818.3 |
| MSE |
2.46187e+09 |
| RMSE |
49617.2 |
| R2 |
-0.000134296 |
| MAPE |
2.94722 |
Learning curves
True vs Predicted
Predicted vs Residuals
<< Go back
Summary of 2_DecisionTree
<< Go back
Decision Tree
- n_jobs: -1
- criterion: squared_error
- max_depth: 3
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
35.4 seconds
Metric details:
| Metric |
Score |
| MAE |
43112.8 |
| MSE |
2.5051e+09 |
| RMSE |
50051 |
| R2 |
-0.0176959 |
| MAPE |
2.96257 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
SHAP Importance
SHAP Dependence plots
Dependence (Fold 1)
SHAP Decision plots
Top-10 Worst decisions (Fold 1)
Top-10 Best decisions (Fold 1)
<< Go back
Summary of 3_Default_Xgboost
<< Go back
Extreme Gradient Boosting (Xgboost)
- n_jobs: -1
- objective: reg:squarederror
- eta: 0.075
- max_depth: 6
- min_child_weight: 1
- subsample: 1.0
- colsample_bytree: 1.0
- eval_metric: rmse
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
7.0 seconds
Metric details:
| Metric |
Score |
| MAE |
42824 |
| MSE |
2.46225e+09 |
| RMSE |
49621 |
| R2 |
-0.000287535 |
| MAPE |
2.94881 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
SHAP Importance
SHAP Dependence plots
Dependence (Fold 1)
SHAP Decision plots
Top-10 Worst decisions (Fold 1)
Top-10 Best decisions (Fold 1)
<< Go back
Summary of 4_Default_NeuralNetwork
<< Go back
Neural Network
- n_jobs: -1
- dense_1_size: 32
- dense_2_size: 16
- learning_rate: 0.05
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
1.6 seconds
Metric details:
| Metric |
Score |
| MAE |
42948.1 |
| MSE |
2.48727e+09 |
| RMSE |
49872.5 |
| R2 |
-0.0104522 |
| MAPE |
2.91167 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
<< Go back
Summary of 5_Default_RandomForest
<< Go back
Random Forest
- n_jobs: -1
- criterion: squared_error
- max_features: 0.9
- min_samples_split: 30
- max_depth: 4
- eval_metric_name: rmse
- explain_level: 2
Validation
- validation_type: split
- train_ratio: 0.75
- shuffle: True
Optimized metric
rmse
Training time
11.6 seconds
Metric details:
| Metric |
Score |
| MAE |
42759.2 |
| MSE |
2.45561e+09 |
| RMSE |
49554.1 |
| R2 |
0.00240879 |
| MAPE |
2.94343 |
Learning curves
Permutation-based Importance
True vs Predicted
Predicted vs Residuals
SHAP Importance
SHAP Dependence plots
Dependence (Fold 1)
SHAP Decision plots
Top-10 Worst decisions (Fold 1)
Top-10 Best decisions (Fold 1)
<< Go back
Summary of Ensemble
<< Go back
Ensemble structure
| Model |
Weight |
| 5_Default_RandomForest |
1 |
Metric details:
| Metric |
Score |
| MAE |
42759.2 |
| MSE |
2.45561e+09 |
| RMSE |
49554.1 |
| R2 |
0.00240879 |
| MAPE |
2.94343 |
Learning curves
True vs Predicted
Predicted vs Residuals
<< Go back